In [206]:
%tensorflow_version 2.x
import tensorflow
tensorflow.__version__
Out[206]:
'2.3.0'
In [207]:
%matplotlib inline
import pandas as pd
import numpy as np
import tensorflow as tf
from google.colab import files
import seaborn as sns
from sklearn.model_selection import train_test_split
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense
from sklearn import metrics
from sklearn.metrics import accuracy_score, confusion_matrix, precision_score, recall_score, f1_score, precision_recall_curve, auc
#uploaded = files.upload()
#uploaded = files.upload()
Pre-Processing Image Data
In [208]:
import numpy as np
Data = pd.read_csv("Labels.csv")
Data.shape
Out[208]:
(4750, 1)
In [209]:
img_array = np.load("images.npy", allow_pickle=True)
In [210]:
img_array.shape
Out[210]:
(4750, 128, 128, 3)
In [211]:
from matplotlib import pyplot as plt
fig, axes = plt.subplots(10, 10, figsize=(100,100))
for i, ax in enumerate(axes.flat):
ax.imshow(img_array[i])
Visualizing of Images
In [212]:
X_data = np.array(img_array[:,:,0,0])
In [213]:
X_data.shape
Out[213]:
(4750, 128)
In [214]:
y_data = Data
In [215]:
y_data.shape
Out[215]:
(4750, 1)
In [216]:
X_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size = 0.3, random_state = 7)
In [217]:
from sklearn import preprocessing
X_train = preprocessing.normalize(X_train)
In [218]:
print(X_train.shape)
print(X_test.shape)
print(y_train.shape)
print(y_test.shape)
(3325, 128) (1425, 128) (3325, 1) (1425, 1)
In [219]:
X_train = X_train.astype('float32')
X_test = X_test.astype('float32')
X_train /= 255
X_test /= 255
In [220]:
print("X_train shape:", X_train.shape)
print("Images in X_train:", X_train.shape[0])
print("Images in X_test:", X_test.shape[0])
print("Max value in X_train:", X_train.max())
print("Min value in X_train:", X_train.min())
X_train shape: (3325, 128) Images in X_train: 3325 Images in X_test: 1425 Max value in X_train: 0.0014285049 Min value in X_train: 0.0
In [221]:
import cv2
from matplotlib import pyplot as plt
img_array = np.load("images.npy", allow_pickle=True)
fig, axes = plt.subplots(10, 10, figsize=(100,100))
for i, ax in enumerate(axes.flat):
gaussian = cv2.GaussianBlur(img_array[i], (15, 15), 0)
ax.imshow(gaussian)
Data Compatibility
In [222]:
from sklearn.preprocessing import LabelBinarizer
enc = LabelBinarizer()
y_train = enc.fit_transform(y_train)
y_test = enc.fit_transform(y_test)
print("Shape of y_train:", y_train.shape)
print("One value of y_train:", y_train[0])
Shape of y_train: (3325, 12) One value of y_train: [0 0 0 1 0 0 0 0 0 0 0 0]
In [223]:
X_test, X_validation, y_test, y_validation = train_test_split(X_test, y_test, test_size = 0.5, random_state = 7)
In [224]:
validation_data = (X_validation, y_validation)
In [225]:
print(X_train.shape)
print(X_test.shape)
print(y_train.shape)
print(y_test.shape)
(3325, 128) (712, 128) (3325, 12) (712, 12)
In [226]:
print(X_train[1])
[0.00057647 0.00054154 0.0005328 0.0005328 0.00051533 0.00048913 0.00046293 0.00051533 0.0005328 0.00048913 0.00044546 0.00040178 0.00041052 0.00042799 0.00042799 0.00040178 0.00039305 0.00034938 0.00028824 0.00035811 0.00037558 0.00035811 0.00032317 0.00035811 0.00036685 0.00037558 0.00038432 0.00038432 0.00039305 0.00036685 0.00034938 0.00035811 0.00033191 0.00036685 0.00033191 0.00033191 0.00029697 0.0002795 0.00027077 0.00026203 0.0002795 0.00028824 0.00028824 0.00034938 0.00041052 0.00047166 0.00047166 0.00038432 0.00019216 0.00020089 0.00030571 0.00032317 0.00030571 0.00032317 0.00033191 0.00032317 0.00040178 0.00033191 0.00028824 0.00032317 0.00032317 0.00032317 0.00031444 0.00031444 0.00031444 0.00030571 0.00029697 0.00030571 0.00029697 0.00031444 0.00043672 0.00048039 0.00037558 0.00033191 0.00031444 0.00030571 0.00028824 0.00028824 0.0002533 0.00023583 0.00026203 0.0002795 0.00027077 0.0002271 0.0002271 0.0002271 0.0002271 0.00023583 0.00023583 0.0002533 0.0002533 0.00024456 0.0002271 0.00023583 0.0002795 0.00030571 0.00035811 0.00039305 0.00035811 0.0002795 0.00034938 0.00029697 0.00027077 0.00034938 0.00031444 0.00032317 0.00021836 0.00020963 0.00026203 0.00032317 0.00031444 0.00028824 0.00033191 0.00035811 0.00034938 0.00029697 0.0002533 0.00026203 0.00026203 0.00034064 0.00038432 0.00038432 0.00039305 0.00041925 0.00033191 0.00028824 0.00034064 0.00032317]
In [227]:
X_train = X_train.reshape((X_train.shape[0], 128)).astype('float32')
X_test = X_test.reshape(X_test.shape[0], 128).astype('float32')
print(X_train.shape)
print(X_test.shape)
(3325, 128) (712, 128)
In [228]:
X_train = np.expand_dims(X_train, axis = 2)
print(X_train.shape)
print(X_test.shape)
(3325, 128, 1) (712, 128)
Building CNN
In [229]:
from tensorflow.keras import datasets, models, layers, optimizers
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping
from google.colab.patches import cv2_imshow
In [230]:
# Set the CNN model
batch_size = None
model = models.Sequential()
model.add(layers.Conv2D(32, (5, 5), padding='same', activation="relu", input_shape=(128,128,1),data_format='channels_first'))
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D((2, 2)))
model.add(layers.Dropout(0.2))
model.add(layers.Conv2D(64, (5, 5), padding='same', activation="relu"))
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D((2, 2)))
model.add(layers.Dropout(0.3))
model.add(layers.Conv2D(64, (3, 3), padding='same', activation="relu"))
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D((2, 2)))
model.add(layers.Dropout(0.4))
model.add(layers.Conv2D(64, (3, 3), padding='same', activation="relu"))
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D((2, 2)))
model.add(layers.Dropout(0.5))
model.add(layers.GlobalMaxPooling2D())
model.add(layers.Dense(256, activation="relu"))
model.add(layers.Dropout(0.5))
model.add(layers.Dense(10, activation="softmax"))
model.summary()
Model: "sequential_18" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= conv2d_20 (Conv2D) (None, 32, 128, 1) 102432 _________________________________________________________________ batch_normalization_20 (Batc (None, 32, 128, 1) 4 _________________________________________________________________ max_pooling2d_20 (MaxPooling (None, 16, 64, 1) 0 _________________________________________________________________ dropout_25 (Dropout) (None, 16, 64, 1) 0 _________________________________________________________________ conv2d_21 (Conv2D) (None, 16, 64, 64) 1664 _________________________________________________________________ batch_normalization_21 (Batc (None, 16, 64, 64) 256 _________________________________________________________________ max_pooling2d_21 (MaxPooling (None, 8, 32, 64) 0 _________________________________________________________________ dropout_26 (Dropout) (None, 8, 32, 64) 0 _________________________________________________________________ conv2d_22 (Conv2D) (None, 8, 32, 64) 36928 _________________________________________________________________ batch_normalization_22 (Batc (None, 8, 32, 64) 256 _________________________________________________________________ max_pooling2d_22 (MaxPooling (None, 4, 16, 64) 0 _________________________________________________________________ dropout_27 (Dropout) (None, 4, 16, 64) 0 _________________________________________________________________ conv2d_23 (Conv2D) (None, 4, 16, 64) 36928 _________________________________________________________________ batch_normalization_23 (Batc (None, 4, 16, 64) 256 _________________________________________________________________ max_pooling2d_23 (MaxPooling (None, 2, 8, 64) 0 _________________________________________________________________ dropout_28 (Dropout) (None, 2, 8, 64) 0 _________________________________________________________________ global_max_pooling2d_5 (Glob (None, 64) 0 _________________________________________________________________ dense_33 (Dense) (None, 256) 16640 _________________________________________________________________ dropout_29 (Dropout) (None, 256) 0 _________________________________________________________________ dense_34 (Dense) (None, 10) 2570 ================================================================= Total params: 197,934 Trainable params: 197,548 Non-trainable params: 386 _________________________________________________________________
In [231]:
opt = optimizers.Adam(learning_rate=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-08)
In [232]:
model.compile(loss='categorical_crossentropy',
optimizer=opt,
metrics=['accuracy'])
In [233]:
model.summary()
Model: "sequential_18" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= conv2d_20 (Conv2D) (None, 32, 128, 1) 102432 _________________________________________________________________ batch_normalization_20 (Batc (None, 32, 128, 1) 4 _________________________________________________________________ max_pooling2d_20 (MaxPooling (None, 16, 64, 1) 0 _________________________________________________________________ dropout_25 (Dropout) (None, 16, 64, 1) 0 _________________________________________________________________ conv2d_21 (Conv2D) (None, 16, 64, 64) 1664 _________________________________________________________________ batch_normalization_21 (Batc (None, 16, 64, 64) 256 _________________________________________________________________ max_pooling2d_21 (MaxPooling (None, 8, 32, 64) 0 _________________________________________________________________ dropout_26 (Dropout) (None, 8, 32, 64) 0 _________________________________________________________________ conv2d_22 (Conv2D) (None, 8, 32, 64) 36928 _________________________________________________________________ batch_normalization_22 (Batc (None, 8, 32, 64) 256 _________________________________________________________________ max_pooling2d_22 (MaxPooling (None, 4, 16, 64) 0 _________________________________________________________________ dropout_27 (Dropout) (None, 4, 16, 64) 0 _________________________________________________________________ conv2d_23 (Conv2D) (None, 4, 16, 64) 36928 _________________________________________________________________ batch_normalization_23 (Batc (None, 4, 16, 64) 256 _________________________________________________________________ max_pooling2d_23 (MaxPooling (None, 2, 8, 64) 0 _________________________________________________________________ dropout_28 (Dropout) (None, 2, 8, 64) 0 _________________________________________________________________ global_max_pooling2d_5 (Glob (None, 64) 0 _________________________________________________________________ dense_33 (Dense) (None, 256) 16640 _________________________________________________________________ dropout_29 (Dropout) (None, 256) 0 _________________________________________________________________ dense_34 (Dense) (None, 10) 2570 ================================================================= Total params: 197,934 Trainable params: 197,548 Non-trainable params: 386 _________________________________________________________________
Evaluate the model.
Hi, last night, my model.fit function stopped working all of a sudden. I am not able to make even the mentor session examples work. In order for my code to compile, I am using a really simple model. This is my original code: model1.fit( x = X_train, y=y_train, batch_size=128, epochs=10, validation_split = 0.5). It worked up until some point, and then it is not. I tried classroom examples too and am getting errors. I can't make this code work with the simplified model: scores = model2.evaluate(x, y, verbose=1) print('Test loss:', scores[0]) print('Test accuracy:', scores[1]).
In [234]:
model2 = Sequential()
model2.add(Dense(1, input_shape=(1,)))
model2.compile(loss='mse', optimizer='rmsprop')
# The fit() method - trains the model
x = np.random.uniform(0.0, 1.0, (200))
y = 0.3 + 0.6*x + np.random.normal(0.0, 0.05,(200))
model2.fit(x, y, epochs=1000, batch_size=100)
Epoch 1/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.8575 Epoch 2/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.8445 Epoch 3/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.8353 Epoch 4/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.8275 Epoch 5/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.8204 Epoch 6/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.8139 Epoch 7/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.8077 Epoch 8/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.8017 Epoch 9/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7960 Epoch 10/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7903 Epoch 11/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.7848 Epoch 12/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7794 Epoch 13/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7741 Epoch 14/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7688 Epoch 15/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7636 Epoch 16/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7584 Epoch 17/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7533 Epoch 18/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7482 Epoch 19/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7432 Epoch 20/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7381 Epoch 21/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7332 Epoch 22/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7282 Epoch 23/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7232 Epoch 24/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7183 Epoch 25/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.7134 Epoch 26/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7085 Epoch 27/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.7036 Epoch 28/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6988 Epoch 29/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6939 Epoch 30/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6891 Epoch 31/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6844 Epoch 32/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.6796 Epoch 33/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6748 Epoch 34/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6701 Epoch 35/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6654 Epoch 36/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6607 Epoch 37/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6560 Epoch 38/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6514 Epoch 39/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6468 Epoch 40/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6421 Epoch 41/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6375 Epoch 42/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6330 Epoch 43/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.6284 Epoch 44/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6238 Epoch 45/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6193 Epoch 46/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6148 Epoch 47/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6103 Epoch 48/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6058 Epoch 49/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.6013 Epoch 50/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5969 Epoch 51/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5925 Epoch 52/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5881 Epoch 53/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5837 Epoch 54/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5793 Epoch 55/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.5749 Epoch 56/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5706 Epoch 57/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5663 Epoch 58/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5620 Epoch 59/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.5577 Epoch 60/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5534 Epoch 61/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.5492 Epoch 62/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5450 Epoch 63/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.5407 Epoch 64/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5365 Epoch 65/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.5324 Epoch 66/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5282 Epoch 67/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.5241 Epoch 68/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5199 Epoch 69/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5158 Epoch 70/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5117 Epoch 71/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.5077 Epoch 72/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.5036 Epoch 73/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4996 Epoch 74/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4956 Epoch 75/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4916 Epoch 76/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4876 Epoch 77/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4836 Epoch 78/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4797 Epoch 79/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4757 Epoch 80/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4718 Epoch 81/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4679 Epoch 82/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4641 Epoch 83/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4602 Epoch 84/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4563 Epoch 85/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4525 Epoch 86/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4487 Epoch 87/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4449 Epoch 88/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4411 Epoch 89/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4374 Epoch 90/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4336 Epoch 91/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4299 Epoch 92/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4262 Epoch 93/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4225 Epoch 94/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4189 Epoch 95/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4152 Epoch 96/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4116 Epoch 97/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4080 Epoch 98/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.4044 Epoch 99/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.4008 Epoch 100/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3973 Epoch 101/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3937 Epoch 102/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3902 Epoch 103/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3867 Epoch 104/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3832 Epoch 105/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3797 Epoch 106/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3763 Epoch 107/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3728 Epoch 108/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3694 Epoch 109/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3660 Epoch 110/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3626 Epoch 111/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3593 Epoch 112/1000 2/2 [==============================] - 0s 5ms/step - loss: 0.3559 Epoch 113/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3526 Epoch 114/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3493 Epoch 115/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3460 Epoch 116/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3427 Epoch 117/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3395 Epoch 118/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3362 Epoch 119/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3330 Epoch 120/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3298 Epoch 121/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3266 Epoch 122/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.3234 Epoch 123/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.3202 Epoch 124/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3171 Epoch 125/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.3140 Epoch 126/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3109 Epoch 127/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3078 Epoch 128/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3047 Epoch 129/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.3017 Epoch 130/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2987 Epoch 131/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2956 Epoch 132/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2927 Epoch 133/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2897 Epoch 134/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2867 Epoch 135/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2838 Epoch 136/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2808 Epoch 137/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2779 Epoch 138/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2750 Epoch 139/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2722 Epoch 140/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2693 Epoch 141/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2665 Epoch 142/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2637 Epoch 143/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2609 Epoch 144/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2581 Epoch 145/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2553 Epoch 146/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2525 Epoch 147/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2498 Epoch 148/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2471 Epoch 149/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2444 Epoch 150/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2417 Epoch 151/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2390 Epoch 152/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2364 Epoch 153/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.2338 Epoch 154/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2311 Epoch 155/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.2285 Epoch 156/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2260 Epoch 157/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2234 Epoch 158/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2209 Epoch 159/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2184 Epoch 160/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2159 Epoch 161/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2134 Epoch 162/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2109 Epoch 163/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.2084 Epoch 164/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.2060 Epoch 165/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2036 Epoch 166/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.2012 Epoch 167/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1988 Epoch 168/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1964 Epoch 169/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1941 Epoch 170/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1917 Epoch 171/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1894 Epoch 172/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.1871 Epoch 173/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1848 Epoch 174/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1826 Epoch 175/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1803 Epoch 176/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1781 Epoch 177/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1759 Epoch 178/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1737 Epoch 179/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1715 Epoch 180/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1694 Epoch 181/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1672 Epoch 182/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1651 Epoch 183/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1630 Epoch 184/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1609 Epoch 185/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1588 Epoch 186/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1568 Epoch 187/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1547 Epoch 188/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1527 Epoch 189/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1507 Epoch 190/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1487 Epoch 191/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1468 Epoch 192/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1448 Epoch 193/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1429 Epoch 194/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1410 Epoch 195/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1391 Epoch 196/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1372 Epoch 197/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1353 Epoch 198/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1334 Epoch 199/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1316 Epoch 200/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1298 Epoch 201/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1280 Epoch 202/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1262 Epoch 203/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1245 Epoch 204/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1227 Epoch 205/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1210 Epoch 206/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1193 Epoch 207/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1176 Epoch 208/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1159 Epoch 209/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1143 Epoch 210/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1126 Epoch 211/1000 2/2 [==============================] - 0s 5ms/step - loss: 0.1110 Epoch 212/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1094 Epoch 213/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1078 Epoch 214/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1062 Epoch 215/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.1047 Epoch 216/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1031 Epoch 217/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1016 Epoch 218/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.1001 Epoch 219/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0986 Epoch 220/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0972 Epoch 221/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0957 Epoch 222/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0943 Epoch 223/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0929 Epoch 224/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0915 Epoch 225/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0901 Epoch 226/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0887 Epoch 227/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0873 Epoch 228/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0860 Epoch 229/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0847 Epoch 230/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0834 Epoch 231/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0821 Epoch 232/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0809 Epoch 233/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0796 Epoch 234/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0784 Epoch 235/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0772 Epoch 236/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0760 Epoch 237/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0748 Epoch 238/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0736 Epoch 239/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0725 Epoch 240/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0714 Epoch 241/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0702 Epoch 242/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0691 Epoch 243/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0681 Epoch 244/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0670 Epoch 245/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0660 Epoch 246/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0649 Epoch 247/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0639 Epoch 248/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0629 Epoch 249/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0619 Epoch 250/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0610 Epoch 251/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0600 Epoch 252/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0591 Epoch 253/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0582 Epoch 254/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0573 Epoch 255/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0564 Epoch 256/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0555 Epoch 257/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0546 Epoch 258/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0538 Epoch 259/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0530 Epoch 260/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0522 Epoch 261/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0514 Epoch 262/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0506 Epoch 263/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0499 Epoch 264/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0491 Epoch 265/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0484 Epoch 266/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0477 Epoch 267/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0470 Epoch 268/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0464 Epoch 269/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0457 Epoch 270/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0451 Epoch 271/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0444 Epoch 272/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0438 Epoch 273/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0432 Epoch 274/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0427 Epoch 275/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0421 Epoch 276/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0415 Epoch 277/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0410 Epoch 278/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0405 Epoch 279/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0400 Epoch 280/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0395 Epoch 281/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0390 Epoch 282/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0386 Epoch 283/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0381 Epoch 284/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0377 Epoch 285/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0373 Epoch 286/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0369 Epoch 287/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0365 Epoch 288/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0361 Epoch 289/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0358 Epoch 290/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0354 Epoch 291/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0351 Epoch 292/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0348 Epoch 293/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0345 Epoch 294/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0342 Epoch 295/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0339 Epoch 296/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0336 Epoch 297/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0333 Epoch 298/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0331 Epoch 299/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0328 Epoch 300/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0326 Epoch 301/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0324 Epoch 302/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0322 Epoch 303/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0320 Epoch 304/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0318 Epoch 305/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0316 Epoch 306/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0314 Epoch 307/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0312 Epoch 308/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0310 Epoch 309/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0308 Epoch 310/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0307 Epoch 311/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0305 Epoch 312/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0303 Epoch 313/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0302 Epoch 314/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0300 Epoch 315/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0298 Epoch 316/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0296 Epoch 317/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0295 Epoch 318/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0293 Epoch 319/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0291 Epoch 320/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0289 Epoch 321/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0287 Epoch 322/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0285 Epoch 323/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0284 Epoch 324/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0282 Epoch 325/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0280 Epoch 326/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0279 Epoch 327/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0277 Epoch 328/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0275 Epoch 329/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0274 Epoch 330/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0271 Epoch 331/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0270 Epoch 332/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0268 Epoch 333/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0266 Epoch 334/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0265 Epoch 335/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0263 Epoch 336/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0262 Epoch 337/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0260 Epoch 338/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0258 Epoch 339/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0257 Epoch 340/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0255 Epoch 341/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0253 Epoch 342/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0252 Epoch 343/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0250 Epoch 344/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0248 Epoch 345/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0246 Epoch 346/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0245 Epoch 347/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0243 Epoch 348/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0241 Epoch 349/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0240 Epoch 350/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0238 Epoch 351/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0236 Epoch 352/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0235 Epoch 353/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0233 Epoch 354/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0232 Epoch 355/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0230 Epoch 356/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0229 Epoch 357/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0227 Epoch 358/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0225 Epoch 359/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0223 Epoch 360/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0222 Epoch 361/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0221 Epoch 362/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0219 Epoch 363/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0217 Epoch 364/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0216 Epoch 365/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0214 Epoch 366/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0213 Epoch 367/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0211 Epoch 368/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0210 Epoch 369/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0208 Epoch 370/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0207 Epoch 371/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0205 Epoch 372/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0204 Epoch 373/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0202 Epoch 374/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0200 Epoch 375/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0199 Epoch 376/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0198 Epoch 377/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0196 Epoch 378/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0195 Epoch 379/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0193 Epoch 380/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0192 Epoch 381/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0190 Epoch 382/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0189 Epoch 383/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0187 Epoch 384/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0186 Epoch 385/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0184 Epoch 386/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0183 Epoch 387/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0182 Epoch 388/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0180 Epoch 389/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0179 Epoch 390/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0177 Epoch 391/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0176 Epoch 392/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0175 Epoch 393/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0173 Epoch 394/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0172 Epoch 395/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0170 Epoch 396/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0169 Epoch 397/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0168 Epoch 398/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0166 Epoch 399/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0165 Epoch 400/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0164 Epoch 401/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0162 Epoch 402/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0161 Epoch 403/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0160 Epoch 404/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0158 Epoch 405/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0157 Epoch 406/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0156 Epoch 407/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0154 Epoch 408/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0153 Epoch 409/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0152 Epoch 410/1000 2/2 [==============================] - 0s 8ms/step - loss: 0.0151 Epoch 411/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0149 Epoch 412/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0148 Epoch 413/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0147 Epoch 414/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0146 Epoch 415/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0144 Epoch 416/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0143 Epoch 417/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0142 Epoch 418/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0141 Epoch 419/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0140 Epoch 420/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0138 Epoch 421/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0137 Epoch 422/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0136 Epoch 423/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0135 Epoch 424/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0134 Epoch 425/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0132 Epoch 426/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0131 Epoch 427/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0130 Epoch 428/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0129 Epoch 429/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0128 Epoch 430/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0127 Epoch 431/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0126 Epoch 432/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 433/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0123 Epoch 434/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0122 Epoch 435/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0121 Epoch 436/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0120 Epoch 437/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0119 Epoch 438/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0118 Epoch 439/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0117 Epoch 440/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0116 Epoch 441/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0115 Epoch 442/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0114 Epoch 443/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0113 Epoch 444/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0112 Epoch 445/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0111 Epoch 446/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0110 Epoch 447/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0109 Epoch 448/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0107 Epoch 449/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0106 Epoch 450/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0105 Epoch 451/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0104 Epoch 452/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0103 Epoch 453/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0102 Epoch 454/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0101 Epoch 455/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0100 Epoch 456/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0100 Epoch 457/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0098 Epoch 458/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0098 Epoch 459/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0097 Epoch 460/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0096 Epoch 461/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0095 Epoch 462/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0094 Epoch 463/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0093 Epoch 464/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0092 Epoch 465/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0091 Epoch 466/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0090 Epoch 467/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0089 Epoch 468/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0088 Epoch 469/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0088 Epoch 470/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0087 Epoch 471/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0086 Epoch 472/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0085 Epoch 473/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0084 Epoch 474/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0083 Epoch 475/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0082 Epoch 476/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0081 Epoch 477/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0081 Epoch 478/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0080 Epoch 479/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0079 Epoch 480/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0078 Epoch 481/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0077 Epoch 482/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0076 Epoch 483/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0076 Epoch 484/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0075 Epoch 485/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0074 Epoch 486/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0073 Epoch 487/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0073 Epoch 488/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0072 Epoch 489/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0071 Epoch 490/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0070 Epoch 491/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0070 Epoch 492/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0069 Epoch 493/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0068 Epoch 494/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0067 Epoch 495/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0067 Epoch 496/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0066 Epoch 497/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0065 Epoch 498/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0065 Epoch 499/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0064 Epoch 500/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0063 Epoch 501/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0062 Epoch 502/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0062 Epoch 503/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0061 Epoch 504/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0060 Epoch 505/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0060 Epoch 506/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0059 Epoch 507/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0059 Epoch 508/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0058 Epoch 509/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0057 Epoch 510/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0057 Epoch 511/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0056 Epoch 512/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0055 Epoch 513/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0055 Epoch 514/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0054 Epoch 515/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0054 Epoch 516/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0053 Epoch 517/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0052 Epoch 518/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0052 Epoch 519/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0051 Epoch 520/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0051 Epoch 521/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0050 Epoch 522/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0050 Epoch 523/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0049 Epoch 524/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0049 Epoch 525/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0048 Epoch 526/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0047 Epoch 527/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0047 Epoch 528/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0047 Epoch 529/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0046 Epoch 530/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0045 Epoch 531/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0045 Epoch 532/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0044 Epoch 533/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0044 Epoch 534/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0044 Epoch 535/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0043 Epoch 536/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0043 Epoch 537/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0042 Epoch 538/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0042 Epoch 539/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0041 Epoch 540/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0041 Epoch 541/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0040 Epoch 542/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0040 Epoch 543/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0039 Epoch 544/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0039 Epoch 545/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0039 Epoch 546/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0038 Epoch 547/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0038 Epoch 548/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0038 Epoch 549/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0037 Epoch 550/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0037 Epoch 551/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0036 Epoch 552/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0036 Epoch 553/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0036 Epoch 554/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0035 Epoch 555/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0035 Epoch 556/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0035 Epoch 557/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0034 Epoch 558/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0034 Epoch 559/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0034 Epoch 560/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0033 Epoch 561/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0033 Epoch 562/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0033 Epoch 563/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0032 Epoch 564/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0032 Epoch 565/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0032 Epoch 566/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0032 Epoch 567/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0031 Epoch 568/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0031 Epoch 569/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0031 Epoch 570/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0030 Epoch 571/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0030 Epoch 572/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0030 Epoch 573/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0030 Epoch 574/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0030 Epoch 575/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0029 Epoch 576/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0029 Epoch 577/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0029 Epoch 578/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0029 Epoch 579/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0028 Epoch 580/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0028 Epoch 581/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0028 Epoch 582/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0028 Epoch 583/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0028 Epoch 584/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0028 Epoch 585/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 586/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 587/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 588/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 589/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 590/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0027 Epoch 591/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 592/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0026 Epoch 593/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 594/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0026 Epoch 595/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0026 Epoch 596/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 597/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 598/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 599/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 600/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0026 Epoch 601/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 602/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 603/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 604/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 605/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 606/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 607/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 608/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 609/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 610/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 611/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 612/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 613/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 614/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 615/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 616/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0025 Epoch 617/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 618/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 619/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0025 Epoch 620/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 621/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 622/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 623/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 624/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 625/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 626/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 627/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 628/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 629/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 630/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 631/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 632/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 633/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 634/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 635/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 636/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 637/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 638/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 639/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 640/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 641/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 642/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 643/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 644/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 645/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 646/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 647/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 648/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 649/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 650/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 651/1000 2/2 [==============================] - 0s 7ms/step - loss: 0.0024 Epoch 652/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 653/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 654/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 655/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 656/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 657/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 658/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 659/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 660/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 661/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 662/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 663/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 664/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 665/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 666/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 667/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 668/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 669/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 670/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 671/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 672/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 673/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 674/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 675/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 676/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 677/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 678/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 679/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 680/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 681/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 682/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 683/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 684/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 685/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 686/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 687/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 688/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 689/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 690/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 691/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 692/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 693/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 694/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 695/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 696/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 697/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 698/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 699/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 700/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 701/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 702/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 703/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 704/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 705/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 706/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 707/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 708/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 709/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 710/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 711/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 712/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 713/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 714/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 715/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 716/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 717/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 718/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 719/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 720/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 721/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 722/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 723/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 724/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 725/1000 2/2 [==============================] - 0s 7ms/step - loss: 0.0024 Epoch 726/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 727/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 728/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 729/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 730/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 731/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 732/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 733/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 734/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 735/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 736/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 737/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 738/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 739/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 740/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 741/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 742/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 743/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 744/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 745/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 746/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 747/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 748/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 749/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 750/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 751/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 752/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 753/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 754/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 755/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 756/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 757/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 758/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 759/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 760/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 761/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 762/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 763/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 764/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 765/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0024 Epoch 766/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 767/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 768/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 769/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 770/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 771/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 772/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 773/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 774/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 775/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 776/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 777/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 778/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 779/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 780/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 781/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0024 Epoch 782/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 783/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 784/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 785/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 786/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 787/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 788/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 789/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 790/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 791/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 792/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 793/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 794/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 795/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 796/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 797/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 798/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 799/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 800/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 801/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 802/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 803/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 804/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 805/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 806/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 807/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 808/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 809/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 810/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 811/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 812/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 813/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 814/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 815/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 816/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 817/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 818/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 819/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 820/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 821/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 822/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 823/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 824/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 825/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 826/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 827/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 828/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 829/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 830/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 831/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 832/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 833/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 834/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 835/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 836/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 837/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 838/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 839/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 840/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 841/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 842/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 843/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 844/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 845/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 846/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 847/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 848/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 849/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 850/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 851/1000 2/2 [==============================] - 0s 5ms/step - loss: 0.0024 Epoch 852/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 853/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 854/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 855/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 856/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 857/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 858/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 859/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 860/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 861/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 862/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 863/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 864/1000 2/2 [==============================] - 0s 5ms/step - loss: 0.0024 Epoch 865/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 866/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 867/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 868/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 869/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 870/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 871/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 872/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 873/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 874/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 875/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 876/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 877/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 878/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 879/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 880/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 881/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 882/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 883/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 884/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 885/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 886/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 887/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 888/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 889/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 890/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 891/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 892/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 893/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 894/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 895/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 896/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 897/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 898/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 899/1000 2/2 [==============================] - 0s 7ms/step - loss: 0.0024 Epoch 900/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 901/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 902/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 903/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 904/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 905/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 906/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 907/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 908/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 909/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 910/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 911/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 912/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 913/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 914/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 915/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 916/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 917/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 918/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 919/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 920/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 921/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 922/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 923/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 924/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 925/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 926/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 927/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 928/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 929/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 930/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 931/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 932/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 933/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 934/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 935/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 936/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 937/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 938/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 939/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 940/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 941/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 942/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 943/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 944/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 945/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 946/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 947/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 948/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 949/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 950/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 951/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 952/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 953/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 954/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 955/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 956/1000 2/2 [==============================] - 0s 1ms/step - loss: 0.0024 Epoch 957/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 958/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 959/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 960/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 961/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 962/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 963/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 964/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 965/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 966/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 967/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 968/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 969/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 970/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 971/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 972/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 973/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 974/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 975/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 976/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 977/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 978/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 979/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 980/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 981/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 982/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 983/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 984/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 985/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 986/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 987/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 988/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 989/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 990/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 991/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 992/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 993/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 994/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 995/1000 2/2 [==============================] - 0s 4ms/step - loss: 0.0024 Epoch 996/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 997/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 998/1000 2/2 [==============================] - 0s 3ms/step - loss: 0.0024 Epoch 999/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024 Epoch 1000/1000 2/2 [==============================] - 0s 2ms/step - loss: 0.0024
Out[234]:
<tensorflow.python.keras.callbacks.History at 0x7f35f52fc320>
In [235]:
results = model2.evaluate(x, y)
Y_pred_cls = model2.predict_classes(y, batch_size=200, verbose=0)
print('Accuracy Model (Dropout): '+ str(model2.evaluate(x,y)))
print('Recall_score: ' + str(recall_score(Y_pred_cls, Y_pred_cls)))
print('Precision_score: ' + str(precision_score(Y_pred_cls, Y_pred_cls)))
print('F-score: ' + str(f1_score(Y_pred_cls,Y_pred_cls)))
conf = confusion_matrix(Y_pred_cls, Y_pred_cls)
sns.heatmap(conf.T, square=True, annot=True, cbar=False, cmap=plt.cm.Blues)
plt.xlabel('Predicted Values')
plt.ylabel('True Values');
plt.show();
7/7 [==============================] - 0s 1ms/step - loss: 0.0024 7/7 [==============================] - 0s 1ms/step - loss: 0.0024 Accuracy Model (Dropout): 0.0024116404820233583 Recall_score: 1.0 Precision_score: 1.0 F-score: 1.0
In [236]:
from keras.utils.vis_utils import plot_model
plot_model(model2, to_file='model_plot.png', show_shapes=True, show_layer_names=True)
Out[236]:
In [237]:
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.9, random_state=0)
y_pred = model2.predict(X_test)
import numpy as np
from matplotlib import pyplot as plt
data = np.array([
[X_test[2], y_pred[2]],
[X_test[3], y_pred[3]],
[X_test[33], y_pred[33]],
[X_test[36], y_pred[36]],
[X_test[59], y_pred[59]],
])
x, y = data.T
plt.scatter(x,y)
plt.show()
